code: def broadcast_to(
      x: Union[tf.Tensor, tf.Variable],
      /,
      shape: Union[ivy.NativeShape, Sequence[int]],
      *,
      out: Optional[Union[tf.Tensor, tf.Variable]] = None,
  ) -> Union[tf.Tensor, tf.Variable]:
      ivy.utils.assertions.check_shapes_broadcastable(x.shape, shape)
      if tf.rank(x) > len(shape):
          return tf.broadcast_to(tf.reshape(x, -1), shape)
      return tf.broadcast_to(x, shape)
  
imports: from typing import Optional, Union, Sequence, List
  import numpy
  import tensorflow
  from tensorflow.python.framework.dtypes import DType
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  from ivy.functional.ivy.data_type import _handle_nestable_dtype_info
  from .None import backend_version
label_desc: Use image node_id 3 for calling a global function with example usage: broadcast_to(shape) and returns: tf, tf